Don't Count Me Out: On the Relevance of IP Address in the Tracking Ecosystem
Vikas Mishra, Pierre Laperdrix, Antoine Vastel, Walter Rudametkin, Romain Rouvoy, Martin Lopatka
摘要
Targeted online advertising has become an inextricable part of the way Web content and applications are monetized. At the beginning, online advertising consisted of simple ad-banners broadly shown to website visitors. Over time, it evolved into a complex ecosystem that tracks and collects a wealth of data to learn user habits and show targeted and personalized ads. To protect users against tracking, several countermeasures have been proposed, ranging from browser extensions that leverage filter lists, to features natively integrated into popular browsers like Firefox and Brave to combat more modern techniques like browser fingerprinting. Nevertheless, few browsers offer protections against IP address-based tracking techniques. Notably, the most popular browsers, Chrome, Firefox, Safari and Edge do not offer any. In this paper, we study the stability of the public IP addresses a user device uses to communicate with our server. Over time, a same device communicates with our server using a set of distinct IP addresses, but we find that devices reuse some of their previous IP addresses for long periods of time. We call this IP address retention and, the duration for which an IP address is retained by a device, is named the IP address retention period. We present an analysis of 34,488 unique public IP addresses collected from 2,230 users over a period of 111 days and we show that IP addresses remain a prime vector for online tracking. 87 % of participants retain at least one IP address for more than a month and 45 % of ISPs in our dataset allow keeping the same IP address for more than 30 days. Furthermore, we also detect the presence of cycles of IP addresses in a user's history and highlight their potential to be abused to infer traits of the user behaviour, as well as mobility traces. Our findings paint a bleak picture of the current state of online tracking at a time where IP addresses are overlooked compared to other techniques like cookies or fingerprinting. CCS CONCEPTS • Security and privacy → Privacy protections; Social aspects of security and privacy.
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引用它的顶会 Paper8
- Privacy Limitations of Interest-based Advertising on The Web: A Post-mortem Empirical Analysis of Google's FLoCAlex Berke, Dan CalacciCCS 2022 · 被引用 8 次
- SoK: After Decades of Web Tracker Detection, What's Next?Wolf Rieder, Philip Raschke, Thomas Cory, Christian René Sechting 等S&P 2026 · 被引用 1 次
- Understanding Server-side Commercial FingerprintingElisa Luo, Tom Ritter, Stefan Savage, Geoffrey M. VoelkerWWW 2026
- Fashion Faux Pas: Implicit Stylistic Fingerprints for Bypassing Browsers' Anti-Fingerprinting DefensesXu Lin, Frederico Araujo, Teryl Taylor, Jiyong Jang 等S&P 2023
- Unleash the Simulacrum: Shifting Browser Realities for Robust Extension-Fingerprinting PreventionSoroush Karami, Faezeh Kalantari, Mehrnoosh Zaeifi, Xavier J. Maso 等USENIX Security 2022
它引用的顶会 Paper6
- Online Tracking: A 1-million-site Measurement and AnalysisSteven Englehardt, Arvind NarayananCCS 2016 · 被引用 798 次
- Beauty and the Beast: Diverting Modern Web Browsers to Build Unique Browser FingerprintsPierre Laperdrix, Walter Rudametkin, Benoit BaudryS&P 2016 · 被引用 279 次
- FP-STALKER: Tracking Browser Fingerprint EvolutionsAntoine Vastel, Pierre Laperdrix, Walter Rudametkin, Romain RouvoyS&P 2018 · 被引用 117 次
- AdGraph: A Graph-Based Approach to Ad and Tracker BlockingUmar Iqbal, Peter Snyder, Shitong Zhu, Benjamin Livshits 等S&P 2020 · 被引用 112 次
- Resident Evil: Understanding Residential IP Proxy as a Dark ServiceXianghang Mi, Xuan Feng, Xiaojing Liao, Baojun Liu 等S&P 2019 · 被引用 80 次
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